Neurotechnology releases SentiMask 2.0 SDK
23 May 2019 12:23 GMT

Neurotechnology, a provider of deep-learning-based solutions, robotics and high-precision biometric identification technologies, today announced the release of the second version of its SentiMask Software Development Kit (SDK) for real-time face tracking and masking, 3D digital character control and other applications.

The SentiMask 2.0 algorithm can detect and track a face in real time from a regular video stream, such as a webcam, or within a video file, and does not require depth sensors or other special hardware. SentiMask 2.0 SDK now includes four different 3D, morphable models of a human face, one of which represents the entire head with the additional three face models varying between different types of topologies and resolutions.

The SentiMask algorithm establishes a user-specific virtual face representation, fitting the models through detection and tracking of specific facial points (landmarks). The established model can be used as an animated avatar, with a 3D face mesh and user-provided textures that respond to, and move in concert with, the user’s facial expressions.

Additionally, the model can be easily augmented with 3D accessories (assets) such as glasses, hats, etc. SentiMask 2.0 will also now detect and recognize attributes such as a user’s gender or age and can establish whether a person is wearing glasses or a hat or has a beard or a mustache. The detected attributes can be used in a wide range of scenarios, from targeted advertising to statistical calculation.

“With the release of SentiMask 2.0 we wanted to widen the list of options developers have to choose from,” said Dr. Vilius Matiukas, SentiMask project lead for Neurotechnology. “We added several different 3D face models as well as additional attribute detection. These new features will expand the number of applications and uses to which SentiMask can contribute.”

In addition to mapping textures onto a person’s face, SentiMask SDK allows users to control the digital characters’ facial expressions, lip movements and head orientation.